Identification

IDNO

GEO_2005_MICS_v01_M

Title

Multiple Indicator Cluster Survey 2005

Translated title

Georgia Multiple Indicator Cluster Survey (MICS) 2005

Countries

Name

Code

Georgia

GEO

Study notes

The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular. MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

Survey Objectives
The 2005 Georgia Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Georgia;
- To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action;
- To contribute to the improvement of data and monitoring systems in Georgia and to strengthen technical expertise in the design, implementation, and analysis of such systems.

Survey Content
MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

Survey Implementation
The survey was carried out by the State Department of Statistics of Georgia and the National Centre for Disease Control of Georgia, with the support and assistance of UNICEF.

Technical assistance and training for the MICS surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

Kind of data

Sample survey data [ssd]

Version

Version

Version 1.0: Edited data used for final report

Version date

2008-01-19

Scope

Topics

Topic

Vocab

Household members

MICS Topics

Education

MICS Topics

Water and sanitation

MICS Topics

Household characteristics

MICS Topics

Child labour

MICS Topics

Child discipline

MICS Topics

Disability

MICS Topics

Salt iodization

MICS Topics

Women's background

MICS Topics

Child mortality

MICS Topics

Maternal and newborn health

MICS Topics

Marriage and union

MICS Topics

Contraception

MICS Topics

Attitudes towards domestic violence

MICS Topics

HIV/AIDS

MICS Topics

Cigarette smoking

Country Specific Topics

Hemoglobin test

Country Specific Topics

Children's background

MICS Topics

Birth registration

MICS Topics

Early learning

MICS Topics

Child development

MICS Topics

Breastfeeding

MICS Topics

Care of illness

MICS Topics

Immunization

MICS Topics

Anthropometry

MICS Topics

Coverage

Geographic coverage

The survey is nationally representative and covers the whole of Georgia.

Unit of analysis

Households (defined as a group of persons who usually live and eat together)

De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)

Women aged 15-49

Children aged 0-4

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Consultancy for preparing data tables, preparation of draft analysis and organizing a seminar for discussing the draft with relevant stakeholders

Turner, Tony

Consultancy for sampling and data weighting

Sampling

Sampling procedure

The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2005 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.

The 2005 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2005 MICS was to prodvide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, and for urban and rural areas separately. In additon, the sample was designed to provide estimates for each of the 11 regions for key indicators. Georgia is devided into 11 regions: Tbilisi, Kakheti, Mtskheta - Mtianeti, Shida Kartli, Kvemo Kartli, Samtskhe - Javakheti, Racha - Lechkhumi and Kvemo, Svaneti, Imereti, Guria, Samegrelo and Zemo Svaneti, Adjara. The sample frame for this survey was based on the list of enumeration areas developed from the 2002 population census.

The primary sampling unit (PSU), the cluster for the 2005 MICS, is defined on the basis of the enumeration areas from the census frame. The minimum PSU size in Georgia is 11 households and the maximum PSU size is 188 households. The average PSU size is 70.8 households. While constructing the sampling frame the PSUs that are smaller then 30 households is merged with the neighbouring PSUs to achieve the minimum size of PSU equalling to 30 households. Although the original sample design for the Georgia MICS 2005 called for approximately 14000 households with an equal number of clusters (42) of households in each of the 11 regions, stratified into urban and rural areas, this sample design was changed to use a more complicated stratification design, with unequal numbers of clusters in each stratum. The rationale for this was for the selection to more closely follow the population distribution of the population.

The sample was selected in four stages and in the first two stages, sample design was stratified according to 11 regions, 3 settlement types (Large town, Small town, and Village), and 4 geographic strata (Valley, Foothills, Mountain, and High mountain). This stratification was applied in all regions, except the city of Tbilisi where the region is stratified according to 10 districts. In total 49 separate strata were identified. The last two stages of the sample design were for the selection of clusters and households.

First stage of sampling: The number of clusters based on sample size calculations was 467 and these were allocated to regions based on the cube root of the number of households in the region. Because the number of clusters for the Racha-Lechkumi region was small (12 clusters), it was decided to increase the number of clusters in that region by 8 for a total of 20 clusters in that region for a total of 475 clusters nationwide.

Second stage of sampling: Within each region, another level of stratification was on a combination of the following: size of settlement (large town, small town, and village) and topography (valley, foothills, mountain, and mountain). The allocation of the number of clusters for a settlement/topography stratum was based on the square root of the number of households in each stratum. Some regions did not have each of the different size settlements or topography. Also, in Tbilisi, the Rayons (districts) were used for stratification.

Third stage of sampling: Within each stratum, clusters were selected with probability proportional to population size (PPS).

Fourth stage of sampling: Within each cluster, 30 households were systematically selected, resulting with 14,250 households.

The Georgia Multiple Indicator Cluster Survey sample is not self-weighted. The basic weighting of the data has been done using the inverse of the probability of selection of each household.

Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewd.

No replacement of households was permitted in case of non-response or non-contactable households. Adjustments were made to the sampling weights to correct for non-response, according to MICS standard procedures.

The sampling procedures are more fully described in the sampling design document and the sampling appendix of the final report.

Deviations from sample design

No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates.

Response rate

Of the 14,250 households selected for the sample, 12,268 were found to be occupied. Of these, 12,010 were successfully interviewed for a household response rate of 97.9 percent. In the interviewed households, 10,908 women (age 15-49) were identified. Of these, 9,847 were successfully interviewed, yielding a response rate of 90.3 percent. In addition, 2,196 children under age five were listed in the household questionnaire. Questionnaires were completed for 2,037 of these children, which corresponds to a response rate of 92.8 percent. Overall response rates of 88.4 and 90.8 are calculated for the women's and under-5's interviews respectively.

Response rates were similar across residence while slight variations in response rates observed by regions. Although the capital city of Tbilisi had the lowest household response rate, the highest response rate for the women questionnaire was found in Tbilisi. The highest response rates for household and children under-5 questionnaires were found in Racha-Lechkhumi and Kvemo Svaneti while Guria region had the lowest response rate for children under-5 questionnaire.

Weighting

Sample weights were calculated for each of the datafiles.

Sample weights for the household data were computed as the inverse of the probability of selection of the household, computed at the sampling domain level (urban/rural within each region). The household weights were adjusted for non-response at the domain level, and were then normalized by a constant factor so that the total weighted number of households equals the total unweighted number of households. The household weight variable is called HHWEIGHT and is used with the HH data and the HL data.

Sample weights for the women's data used the un-normalized household weights, adjusted for non-response for the women's questionnaire, and were then normalized by a constant factor so that the total weighted number of women's cases equals the total unweighted number of women's cases.

Sample weights for the children's data followed the same approach as the women's and used the un-normalized household weights, adjusted for non-response for the children's questionnaire, and were then normalized by a constant factor so that the total weighted number of children's cases equals the total unweighted number of children's cases.

Data Collection

Dates of collection

Start

End

2005-09-11

2005-12-30

Mode of data collection

Face-to-face [f2f]

Data collection supervision

Interviewing was conducted by teams of interviewers. Each interviewing team comprised of five interviewers, two drivers, one editor/measurer and one supervisor. Each team used a 4 wheel drive vehicle to travel from cluster to cluster (and where necessary within cluster).

The role of the supervisor was to coordinate field data collection activities, including management of the field teams, supplies and equipment, finances, maps and listings, coordinate with local authorities concerning the survey plan and make arrangements for accomodation and travel. Additionally, the field supervisor assigned the work to the interviewers, spot checked work, maintained field control documents, and sent completed questionnaires and progress reports to the central office

The field editor was responsible for reviewing each questionnaire at the end of the day, checking for missed questions, skip errors, fields incorrectly completed, and checking for inconsistencies in the data. The field editor also observed interviews and conducted review sessions with interviewers.

Responsibilities of the supervisors and field editors are described in the Instructions for Supervisors and Field Editors, together with the different field controls that were in place to control the quality of the fieldwork.

Questionnaires

The questionnaires for the Georgia MICS were structured questionnaires based on the MICS3 Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status. The household questionnaire includes household listing, education, water and sanitation, household characteristics, child labour, child discipline, disability, and salt iodization.

In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or caretaker of the child.

The children's questionnaire includes birth registration and early learning, child development, breastfeeding, care of illness, immunization*, and anthropometry.

The questionnaires are based on the MICS3 model questionnaire. From the MICS3 model English and Russian versions, the questionnaires were translated into Georgian and were pre-tested in Tbilisi and in Mtskheta-Mtianeti during September 2005. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

*The immunization levels were based primarily on recall and it appeared that the respondents' reporting of the immunizations received and, in particular, the number of doses was under reported. As a result, it was decided that the immunization levels are not reported because of the strong potential for biased estimates.

Data collector(s)

Name

Abbreviation

State Department of Statistics of Georgia

SDS

Data Processing

Data editing

Data editing took place at a number of stages throughout the processing (see Other processing), including:
a) Office editing and coding
b) During data entry
c) Structure checking and completeness
d) Secondary editing
e) Structural checking of SPSS data files

Detailed documentation of the editing of data can be found in the data processing guidelines.

metadata.study_desc.method.data_collection.method_notes

Data were processed in clusters, with each cluster being processed as a complete unit through each stage of data processing. Each cluster goes through the following steps:
1) Questionnaire reception
2) Office editing and coding
3) Data entry
4) Structure and completeness checking
5) Verification entry
6) Comparison of verification data
7) Back up of raw data
8) Secondary editing
9) Edited data back up
After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files:
10) Export to SPSS in 4 files (hh - household, hl - household members, wm - women, ch - children under 5)
11) Recoding of variables needed for analysis
12) Adding of sample weights
13) Calculation of wealth quintiles and merging into data
14) Structural checking of SPSS files
15) Data quality tabulations
16) Production of analysis tabulations

Details of each of these steps can be found in the data processing documentation, data editing guidelines, data processing programs in CSPro and SPSS, and tabulation guidelines.

Data entry was conducted by 3 data entry operators, supervised by 2 data entry supervisors, using a total of 3 computers. All data entry was conducted at the State Department of Statistics of Georgia head office using manual data entry. For data entry, CSPro version 2.6.007 was used with a highly structured data entry program, using system controlled approach, that controlled entry of each variable. All range checks and skips were controlled by the program and operators could not override these. A limited set of consistency checks were also included inthe data entry program. In addition, the calculation of anthropometric Z-scores was also included in the data entry programs for use during analysis. Open-ended responses ("Other" answers) were not entered or coded, except in rare circumstances where the response matched an existing code in the questionnaire.

Structure and completeness checking ensured that all questionnaires for the cluster had been entered, were structurally sound, and that women's and children's questionnaires existed for each eligible woman and child.

100% verification of all variables was performed using independent verification, i.e. double entry of data, with separate comparison of data followed by modification of one or both datasets to correct keying errors by original operators who first keyed the files.

After completion of all processing in CSPro, all individual cluster files were backed up before concatenating data together using the CSPro file concatenate utility.

For tabulation and analysis SPSS version 14.0 was used.

After transferring all files to SPSS, certain variables were recoded for use as background characteristics in the tabulation of the data, including grouping age, education, geographic areas as needed for analysis. In the process of recoding ages and dates some random imputation of dates (within calculated constraints) was performed to handle missing or "don't know" ages or dates. Additionally, a wealth (asset) index of household members was calculated using principal components analysis, based on household assets, and both the score and quintiles were included in the datasets for use in tabulations.

Data Appraisal

metadata.study_desc.method.analysis_info.sampling_error_estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2005 MICS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors can be evaluated statistically. The sample of respondents to the 2005 MICS is only one of many possible samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differe somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability in the results of the survey between all possible samples, and, although, the degree of variability is not known exactly, it can be estimated from the survey results. The sampling erros are measured in terms of the standard error for a particular statistic (mean or percentage), which is the square root of the variance. Confidence intervals are calculated for each statistic within which the true value for the population can be assumed to fall. Plus or minus two standard errors of the statistic is used for key statistics presented in MICS, equivalent to a 95 percent confidence interval.

If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formulae for calculating sampling errors. However, the 2005 MICS sample is the result of a multi-stage stratified design, and consequently needs to use more complex formulae. The SPSS complex samples module has been used to calculate sampling errors for the 2005 MICS. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. This method is documented in the SPSS file CSDescriptives.pdf found under the Help, Algorithms options in SPSS.

Sampling errors have been calculated for a select set of statistics (all of which are proportions due to the limitations of the Taylor linearization method) for the national sample, urban and rural areas, and for each of the 11 regions. For each statistic, the estimate, its standard error, the coefficient of variation (or relative error -- the ratio between the standard error and the estimate), the design effect, and the square root design effect (DEFT -- the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used), as well as the 95 percent confidence intervals (+/-2 standard errors).

Other forms of data appraisal

A series of data quality tables and graphs are available to review the quality of the data and include the following:

Age distribution of the household population
Age distribution of eligible women and interviewed women
Age distribution of eligible children and children for whom the mother or caretaker was interviewed
Age distribution of children under age 5 by 3 month groups
Age and period ratios at boundaries of eligibility
Percent of observations with missing information on selected variables
Presence of mother inthe household and person interviewed for the under 5 questionnaire
School attendance by single year age
Sex ratio at birth among children ever born, surviving and dead by age of respondent
Distribution of women by time since last birth
Scatterplot of weight by height, weight by age and height by age
Graph of male and female population by single years of age
Population pyramid

The general rule for presentation of missing data in the final report tabulations is that a column is presented for missing data if the percentage of cases with missing data is 1% or more. Cases with missing data on the background characteristics (e.g. education) are included in the tables, but the missing data rows are suppressed and noted at the bottom of the tables in the report (not in the SPSS output, however).

Data access

Access authorities

Name

Affiliation

Email

URI

State Department of Statistics of Georgia

www.statistics.ge

Giovanna Barberis

UNICEF, Georgia

gbarberis@unicef.org

www.unicef.org

metadata.study_desc.data_access.dataset_use.conf_dec

Users of the data agree to keep confidential all data contained in these datasets and to make no attempt to identify, trace or contact any individual whose data is included in these datasets.

Access conditions

Survey datasets are distributed at no cost for legitimate research, with the condition that we receive a description of the research objectives that will be using the data prior to authorizing their distribution. Copies of all reports and publications based on the requested data must be sent to: Dimitri Gugushvili, UNICEF Georgia, dgugushvili@unicef.org

Requests for access to the datasets may be made through the website www.childinfo.org.

Disclaimer and copyrights

Disclaimer

State Department of Statistics and UNICEF provide these data to external users without any warranty or responsibility implied. State Department of Statistics and UNICEF accept no responsibility for the results and/or implications of any actions resulting from the use of these data.

Copyrights

2008, State Department of Statistics, Georgia

Contacts

Contact(s)

Name

Affiliation

Email

URI

Paqsashvili, Temur

State Department of Statistics, Ministry of Economic Development of Georgia